Research on Dynamic Obstacle Avoidance and Adaptive Control Strategy of New Unmanned Ship

Abstract

With the rapid development of marine resource exploitation and the growing demand for intelligent shipping, the dynamic obstacle
avoidance capability and autonomous control efficiency of unmanned vessels in complex aquatic environments have become critical bottlenecks hindering their large-scale application. Current unmanned vessel systems predominantly rely on preset navigation paths to avoid obstacles, which proves inadequate for dynamic marine environments. There is an urgent need to establish control systems with real-time perception and adaptive decision-making capabilities. This study focuses on the importance of dynamic obstacle avoidance and innovative control
strategies, proposing a collaborative framework integrating environmental modeling and multi-objective optimization. Through a hierarchical
algorithm architecture, the framework balances obstacle avoidance efficiency with navigation stability. The adaptive control strategy designed
for specific mission scenarios combines local path replanning with global task adjustment mechanisms, providing theoretical support for enhancing the reliability and adaptability of unmanned vessels in uncharted waters. The research findings hold significant practical implications
for advancing intelligent ship technology innovation and ensuring maritime operational safety.